Tsoulaki, O; Tischkowitz, M; Antoniou, AC; Musgrave, H; Rea, G; Gandhi, A; Cox, K; Irvine, T; Holcombe, S; Eccles, D; et al. Tsoulaki, O; Tischkowitz, M; Antoniou, AC; Musgrave, H; Rea, G; Gandhi, A; Cox, K; Irvine, T; Holcombe, S; Eccles, D; Turnbull, C; Cutress, R; Meeting Attendees; Archer, S; Hanson, H (2024) Joint ABS-UKCGG-CanGene-CanVar consensus regarding the use of CanRisk in clinical practice. Br J Cancer, 130 (12). pp. 2027-2036. ISSN 0007-0920 https://doi.org/10.1038/s41416-024-02733-4
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Abstract
BACKGROUND: The CanRisk tool, which operationalises the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is used by Clinical Geneticists, Genetic Counsellors, Breast Oncologists, Surgeons and Family History Nurses for breast cancer risk assessments both nationally and internationally. There are currently no guidelines with respect to the day-to-day clinical application of CanRisk and differing inputs to the model can result in different recommendations for practice. METHODS: To address this gap, the UK Cancer Genetics Group in collaboration with the Association of Breast Surgery and the CanGene-CanVar programme held a workshop on 16th of May 2023, with the aim of establishing best practice guidelines. RESULTS: Using a pre-workshop survey followed by structured discussion and in-meeting polling, we achieved consensus for UK best practice in use of CanRisk in making recommendations for breast cancer surveillance, eligibility for genetic testing and the input of available information to undertake an individualised risk assessment. CONCLUSIONS: Whilst consensus recommendations were achieved, the meeting highlighted some of the barriers limiting the use of CanRisk in clinical practice and identified areas that require further work and collaboration with relevant national bodies and policy makers to incorporate wider use of CanRisk into routine breast cancer risk assessments.
Item Type: | Article | ||||||||||||||||||
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Additional Information: | © The Author(s) 2024 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | ||||||||||||||||||
Keywords: | Humans, Female, Breast Neoplasms, Risk Assessment, Genetic Testing, United Kingdom, Genetic Predisposition to Disease, Consensus, Algorithms, Genetic Counseling | ||||||||||||||||||
SGUL Research Institute / Research Centre: | Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) | ||||||||||||||||||
Journal or Publication Title: | Br J Cancer | ||||||||||||||||||
ISSN: | 0007-0920 | ||||||||||||||||||
Language: | eng | ||||||||||||||||||
Media of Output: | Print-Electronic | ||||||||||||||||||
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Publisher License: | Creative Commons: Attribution 4.0 | ||||||||||||||||||
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URI: | https://openaccess.sgul.ac.uk/id/eprint/117500 | ||||||||||||||||||
Publisher's version: | https://doi.org/10.1038/s41416-024-02733-4 |
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